English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Data stewards seeking to provide access to large-scale social science dataface a difficult challenge. They have to share data in ways that protectprivacy and confidentiality, are informative for many analyses and purposes,and are relatively straightforward to use by data analysts. One approachsuggested in the literature is that data stewards generate and releasesynthetic data, i.e., data simulated from statistical models, while alsoproviding users access to a verification server that allows them to assess thequality of inferences from the synthetic data. We present an application of thesynthetic data plus verification server approach to longitudinal data onemployees of the U.S. federal government. As part of the application, wepresent a novel model for generating synthetic career trajectories, as well asstrategies for generating high dimensional, longitudinal synthetic datasets. Wealso present novel verification algorithms for regression coefficients thatsatisfy differential privacy. We illustrate the integrated use of syntheticdata plus verification via analysis of differentials in pay by race. Theintegrated system performs as intended, allowing users to explore the syntheticdata for potential pay differentials and learn through verifications whichfindings in the synthetic data hold up and which do not. The analysis on theconfidential data reveals pay differentials across races not documented inpublished studies.

Providing Access to Confidential Research Data Through Synthesis and  Verification: An Application to Data on Employees of the U.S. Federal  Government